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Non-invasive Bone Competence Analysis By High-resolution PQCT: An In Vitro Reproducibility Study On Structural And Mechanical Properties At The Human Radius.
T. L. Mueller, M. Stauber, T. Kohler, F. Eckstein, R. Mueller, G. H. van Lenthe
Published 2009 · Materials Science, Medicine
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Osteoporosis is defined as a skeletal disorder characterized by compromised bone strength. Bone strength depends, among others, on bone density, bone geometry and its internal architecture. With the recent introduction of a new generation high-resolution 3D peripheral quantitative computed tomography (HR-pQCT) system, direct quantification of structural bone parameters has become feasible. Furthermore, it has recently been demonstrated that bone mechanical competence can be derived from HR-pQCT based micro-finite element modeling (microFE). However, reproducibility data for HR-pQCT-derived mechanical indices is not well-known. Therefore, the aim of this study was to quantify reproducibility of HR-pQCT-derived indices. We measured 14 distal formalin-fixed cadaveric forearms three times and analyzed three different regions for each measurement. For each region cortical and trabecular parameters were determined. Reproducibility was assessed with respect to precision error (PE) and intraclass correlation coefficient (ICC). Reproducibility values were found to be best in all three regions for the full bone compartment with an average PE of 0.79%, followed by the cortical compartment (PE=1.19%) and the trabecular compartment with an average PE of 2.31%. The mechanical parameters showed similar reproducibility (PE=0.48%-2.93% for bone strength and stiffness, respectively). ICC showed a very high reproducibility of subject-specific measurements, ranging from 0.982 to 1.000, allowing secure identification of individual donors ranging from healthy to severely osteoporotic subjects. From these in vitro results we conclude that HR-pQCT derived morphometric and mechanical parameters are highly reproducible such that differences in bone structure and strength can be detected with a reproducibility error smaller than 3%; hence, the technique has a high potential to become a tool for detecting bone quality and bone competence of individual subjects.
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